{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T03:21:55Z","timestamp":1790220115156,"version":"4.1.0"},"reference-count":70,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T00:00:00Z","timestamp":1783728000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T00:00:00Z","timestamp":1783728000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["101017562"],"award-info":[{"award-number":["101017562"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020989","name":"Gedeon Richter France","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100020989","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017125","name":"Coll\u00e8ge National des Gyn\u00e9cologues et Obst\u00e9triciens Fran\u00e7ais","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100017125","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["obgyn.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Acta Obstet Gynecol Scand"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Material and Methods<\/jats:title>\n                    <jats:p>A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%\u201397%), red lesions (PPV 33%\u2013100%), white lesions (PPV 20%\u201381%), and ovarian endometriosis (PPV 42%\u201398%). Nonspecific lesions such as adhesions (PPV 16%\u201350%) and subtle superficial lesions (PPV 0%\u201367%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/aogs.70293","type":"journal-article","created":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T07:27:48Z","timestamp":1783754868000},"page":"1904-1917","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition"],"prefix":"10.1111","volume":"105","author":[{"given":"Antoine","family":"Netter","sequence":"first","affiliation":[{"name":"Department of Gynecology, Obstetrics and Reproductive Medicine AP\u2010HM, P\u00f4le Femmes Parents Enfants  Marseille France"},{"name":"EA3279, CEReSS, Health Service Research and Quality of Life Center Aix\u2010Marseille University  Marseille France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fanny","family":"Duchateau","sequence":"additional","affiliation":[{"name":"Department of Gynecology, Obstetrics and Reproductive Medicine AP\u2010HM, P\u00f4le Femmes Parents Enfants  Marseille France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henrique","family":"Abrao","sequence":"additional","affiliation":[{"name":"Department of Gynecological Surgery University Hospital Clermont\u2010Ferrand  Clermont\u2010Ferrand France"},{"name":"Department of Clinical Research and Innovation University Hospital Clermont\u2010Ferrand  Clermont Ferrand France"},{"name":"Department of Obstetrics and Gynecology University of S\u00e3o Paulo Medical School  S\u00e3o Paulo Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0852-7811","authenticated-orcid":false,"given":"Michel","family":"Canis","sequence":"additional","affiliation":[{"name":"Department of Gynecological Surgery University Hospital Clermont\u2010Ferrand  Clermont\u2010Ferrand France"},{"name":"Department of Clinical Research and Innovation University Hospital Clermont\u2010Ferrand  Clermont Ferrand France"},{"name":"EnCoV, Institut Pascal, UMR 6602 CNRS\/Universit\u00e9 Clermont\u2010Auvergne  Clermont\u2010Ferrand France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1904-1449","authenticated-orcid":false,"given":"Dan C.","family":"Martin","sequence":"additional","affiliation":[{"name":"University of Tennessee Health Science Center  Memphis Tennessee USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrien","family":"Bartoli","sequence":"additional","affiliation":[{"name":"Department of Clinical Research and Innovation University Hospital Clermont\u2010Ferrand  Clermont Ferrand France"},{"name":"EnCoV, Institut Pascal, UMR 6602 CNRS\/Universit\u00e9 Clermont\u2010Auvergne  Clermont\u2010Ferrand France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Bourdel","sequence":"additional","affiliation":[{"name":"Department of Gynecological Surgery University Hospital Clermont\u2010Ferrand  Clermont\u2010Ferrand France"},{"name":"Department of Clinical Research and Innovation University Hospital Clermont\u2010Ferrand  Clermont Ferrand France"},{"name":"EnCoV, Institut Pascal, UMR 6602 CNRS\/Universit\u00e9 Clermont\u2010Auvergne  Clermont\u2010Ferrand France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"the FEMaLe Project Work Group","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,11]]},"reference":[{"key":"e_1_2_13_2_1","volume-title":"Endometriosis: Diagnosis and Management. 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